Exploring wind data using the Meteostat

Group Members: Travis, Ira, Micah

Course: Data Science

Goal: Use ML models to predict wind trends in distinct U.S. regions

Source: Meteostat Python API

Dataset Type: Aggregated weather observations per station

Key Variables
  • wspd: Average wind speed (mph)
  • wdir: Mean wind direction (degrees)

Time Period: 2024

Models: Wind Speed, Wind Direction, Locations

Frame: Hourly and Daily

Using Pittsburgh station

Missing Values
temp       0
dwpt       0
rhum       0
prcp    1091
snow    8761
wdir       0
wspd       0
wpgt    8761
pres       0
tsun    8761
coco       6
dtype: int64

Lagged 1, 3, and 6 hours before

TimeSeriesSplit with n_splits = 5

Linear Regression
MAE:  3.223
RMSE: 4.351
R²:   0.675

HistGradientBoostingRegressor
MAE:  2.649
RMSE: 3.906
R²:   0.743
  1. How do wind patterns change by region?
  2. What are some case studies of extreme weather?
  3. How do geographical features (lakes, oceans, mountains, deserts, plains) impact wind patterns?